Added results from example 002

fmi-basel · Mar 18, 2022 · c82c146 · c82c146
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diff --git a/config_params.md b/config_params.md
@@ -23,9 +23,9 @@ The configuration file is subdivided into main sections
 ### **4) Cell segmentation**
     Performs cell and lumen (+ epithelium) segmentation model training and prediction tasks on image data, based on predicted nuclei segmentation.
 ### **5) Features**
-    Extracts features based on the segmented label maps
+    Extracts features based on the segmented label maps. Its output is an .h5 file containing the feature table.
 ### **6) Meshes**
-    Creates .vtk meshes based on the cell and nuclei segmentation label maps
+    Creates .vti meshes based on the cell and nuclei segmentation label maps
 ### **7) Tracking**
     Performs tracking model training and prediction tasks on image data based on existing nuclei segmentation.
 

diff --git a/example/README.md b/example/README.md
@@ -19,7 +19,7 @@ Raw images are first denoised with [Noise2Void](https://github.com/juglab/n2v) t
 ```bash
 LUIGI_CONFIG_PATH=./config.cfg luigi --local-scheduler --module lstree MultiDeconvolutionTask
 ```
-> **-Deconv folder requirement**: The outputs from this step include a folder with '-Deconv' as a suffix, and the other steps use the images inside as input for segmentation. If this is not needed, a - so far still hacky - way around it is to copy the raw images to an empty folder with the same name before running the config file.
+> **'-Deconv' folder requirement**: The outputs from this step include a folder with '-Deconv' as a suffix, and the other steps use the images inside as input for segmentation. If this is not needed, i.e. if only raw data is desired to be processed, a - so far still hacky - way around it is to copy the raw images to an empty folder with the same name before running the config file.
 
 > **PSF estimation**: As expected during deconvolution, a point-spread-function (PSF) of the optics used for imaging is necessary. You can uye [Huygens PSF Distiller](https://svi.nl/Huygens-PSF-Distiller) or the [PSF extraction from python-microscopy](http://python-microscopy.org/doc/PSFExtraction.html).
 

diff --git a/example/data/002-Budding/Channel0-Deconv/002-Ch0-T0301.tif b/example/data/002-Budding/Channel0-Deconv/002-Ch0-T0301.tif
diff --git a/example/data/002-Budding/Channel0-Deconv/002-Ch0-T0302.tif b/example/data/002-Budding/Channel0-Deconv/002-Ch0-T0302.tif
diff --git a/example/data/002-Budding/Channel0-Deconv/002-Ch0-T0303.tif b/example/data/002-Budding/Channel0-Deconv/002-Ch0-T0303.tif
diff --git a/example/data/002-Budding/Channel0-Deconv/002-Ch0-T0304.tif b/example/data/002-Budding/Channel0-Deconv/002-Ch0-T0304.tif
diff --git a/example/data/002-Budding/Channel0-Deconv/002-Ch0-T0305.tif b/example/data/002-Budding/Channel0-Deconv/002-Ch0-T0305.tif
diff --git a/example/data/002-Budding/Channel0-Denoised/002-Ch0-T0301.tif b/example/data/002-Budding/Channel0-Denoised/002-Ch0-T0301.tif
diff --git a/example/data/002-Budding/Channel0-Denoised/002-Ch0-T0302.tif b/example/data/002-Budding/Channel0-Denoised/002-Ch0-T0302.tif
diff --git a/example/data/002-Budding/Channel0-Denoised/002-Ch0-T0303.tif b/example/data/002-Budding/Channel0-Denoised/002-Ch0-T0303.tif
diff --git a/example/data/002-Budding/Channel0-Denoised/002-Ch0-T0304.tif b/example/data/002-Budding/Channel0-Denoised/002-Ch0-T0304.tif
diff --git a/example/data/002-Budding/Channel0-Denoised/002-Ch0-T0305.tif b/example/data/002-Budding/Channel0-Denoised/002-Ch0-T0305.tif
diff --git a/example/data/002-Budding/Channel0_bounds.json b/example/data/002-Budding/Channel0_bounds.json
@@ -0,0 +1,5 @@
+{
+    "max": 933,
+    "max_q0.99999": 719,
+    "min": 57
+}
diff --git a/example/data/002-Budding/Channel1-Deconv/002-Ch1-T0301.tif b/example/data/002-Budding/Channel1-Deconv/002-Ch1-T0301.tif
diff --git a/example/data/002-Budding/Channel1-Deconv/002-Ch1-T0302.tif b/example/data/002-Budding/Channel1-Deconv/002-Ch1-T0302.tif
diff --git a/example/data/002-Budding/Channel1-Deconv/002-Ch1-T0303.tif b/example/data/002-Budding/Channel1-Deconv/002-Ch1-T0303.tif
diff --git a/example/data/002-Budding/Channel1-Deconv/002-Ch1-T0304.tif b/example/data/002-Budding/Channel1-Deconv/002-Ch1-T0304.tif
diff --git a/example/data/002-Budding/Channel1-Deconv/002-Ch1-T0305.tif b/example/data/002-Budding/Channel1-Deconv/002-Ch1-T0305.tif
diff --git a/example/data/002-Budding/Channel1-Denoised/002-Ch1-T0301.tif b/example/data/002-Budding/Channel1-Denoised/002-Ch1-T0301.tif
diff --git a/example/data/002-Budding/Channel1-Denoised/002-Ch1-T0302.tif b/example/data/002-Budding/Channel1-Denoised/002-Ch1-T0302.tif
diff --git a/example/data/002-Budding/Channel1-Denoised/002-Ch1-T0303.tif b/example/data/002-Budding/Channel1-Denoised/002-Ch1-T0303.tif
diff --git a/example/data/002-Budding/Channel1-Denoised/002-Ch1-T0304.tif b/example/data/002-Budding/Channel1-Denoised/002-Ch1-T0304.tif
diff --git a/example/data/002-Budding/Channel1-Denoised/002-Ch1-T0305.tif b/example/data/002-Budding/Channel1-Denoised/002-Ch1-T0305.tif
diff --git a/example/data/002-Budding/Channel1_bounds.json b/example/data/002-Budding/Channel1_bounds.json
@@ -0,0 +1,5 @@
+{
+    "max": 938,
+    "max_q0.99999": 782,
+    "min": 73
+}
diff --git a/example/data/002-Budding/agg_features.h5 b/example/data/002-Budding/agg_features.h5
diff --git a/example/data/002-Budding/cell_mesh/002-Ch0-T0301.vtp b/example/data/002-Budding/cell_mesh/002-Ch0-T0301.vtp
diff --git a/example/data/002-Budding/cell_mesh/002-Ch0-T0302.vtp b/example/data/002-Budding/cell_mesh/002-Ch0-T0302.vtp
diff --git a/example/data/002-Budding/cell_mesh/002-Ch0-T0303.vtp b/example/data/002-Budding/cell_mesh/002-Ch0-T0303.vtp
diff --git a/example/data/002-Budding/cell_mesh/002-Ch0-T0304.vtp b/example/data/002-Budding/cell_mesh/002-Ch0-T0304.vtp
diff --git a/example/data/002-Budding/cell_mesh/002-Ch0-T0305.vtp b/example/data/002-Budding/cell_mesh/002-Ch0-T0305.vtp
diff --git a/example/data/002-Budding/cell_segmentation/002-Ch0-T0301.tif b/example/data/002-Budding/cell_segmentation/002-Ch0-T0301.tif
diff --git a/example/data/002-Budding/cell_segmentation/002-Ch0-T0302.tif b/example/data/002-Budding/cell_segmentation/002-Ch0-T0302.tif
diff --git a/example/data/002-Budding/cell_segmentation/002-Ch0-T0303.tif b/example/data/002-Budding/cell_segmentation/002-Ch0-T0303.tif
diff --git a/example/data/002-Budding/cell_segmentation/002-Ch0-T0304.tif b/example/data/002-Budding/cell_segmentation/002-Ch0-T0304.tif
diff --git a/example/data/002-Budding/cell_segmentation/002-Ch0-T0305.tif b/example/data/002-Budding/cell_segmentation/002-Ch0-T0305.tif
diff --git a/example/data/002-Budding/features/T0301.csv b/example/data/002-Budding/features/T0301.csv
@@ -0,0 +1,319 @@
+channel,region,object_id,feature_name,feature_value
+na,cell,1,neighbors,"[5, 7, 11, 2, 3]"
+na,cell,2,neighbors,"[1, 11, 5, 12, 3, 13, 4]"
+na,cell,3,neighbors,"[1, 7, 2, 9, 4, 13, 19, 8]"
+na,cell,4,neighbors,"[2, 3, 13, 7, 19, 8]"
+na,cell,5,neighbors,"[10, 16, 1, 11, 7, 6, 2]"
+na,cell,6,neighbors,"[10, 17, 5, 7, 18, 9, 16]"
+na,cell,7,neighbors,"[5, 10, 6, 1, 9, 3, 8, 4]"
+na,cell,8,neighbors,"[3, 7, 9, 4, 19, 18]"
+na,cell,9,neighbors,"[7, 6, 18, 10, 17, 3, 8, 19, 20]"
+na,cell,10,neighbors,"[5, 16, 17, 6, 7, 18, 9]"
+na,cell,11,neighbors,"[5, 16, 1, 2, 12, 15]"
+na,cell,12,neighbors,"[11, 16, 2, 15, 13, 19]"
+na,cell,13,neighbors,"[2, 12, 15, 3, 4, 19]"
+na,cell,15,neighbors,"[16, 17, 12, 11, 20, 13, 19]"
+na,cell,16,neighbors,"[5, 10, 17, 11, 12, 15, 6, 20]"
+na,cell,17,neighbors,"[16, 10, 6, 18, 9, 15, 20]"
+na,cell,18,neighbors,"[6, 17, 10, 9, 20, 19, 8]"
+na,cell,19,neighbors,"[3, 13, 12, 15, 20, 9, 18, 4, 8]"
+na,cell,20,neighbors,"[16, 17, 15, 18, 19, 9]"
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+nuclei_intensity,nuclei,1,std,10261.447503164069
+nuclei_intensity,nuclei,2,mean,21462.622355289423
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+nuclei_intensity,nuclei,3,std,10908.584880862922
+nuclei_intensity,nuclei,4,mean,25295.961663417806
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+nuclei_intensity,nuclei,6,mean,26935.036182158452
+nuclei_intensity,nuclei,6,std,13571.894635971788
+nuclei_intensity,nuclei,7,mean,25120.17826887661
+nuclei_intensity,nuclei,7,std,12888.703609788077
+nuclei_intensity,nuclei,8,mean,27411.051425377307
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+nuclei_intensity,nuclei,11,mean,32358.618834080717
+nuclei_intensity,nuclei,11,std,16149.412383475246
+nuclei_intensity,nuclei,12,mean,23455.70042194093
+nuclei_intensity,nuclei,12,std,10863.875687065287
+nuclei_intensity,nuclei,13,mean,26289.63272513243
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+nuclei_intensity,nuclei,20,mean,26809.311667723527
+nuclei_intensity,nuclei,20,std,13680.06058561408
+dist_to_lumen,nuclei,1,mean,7.910897254943848
+dist_to_lumen,nuclei,2,mean,9.244121551513672
+dist_to_lumen,nuclei,3,mean,7.493631362915039
+dist_to_lumen,nuclei,4,mean,8.698860168457031
+dist_to_lumen,nuclei,5,mean,7.404200553894043
+dist_to_lumen,nuclei,6,mean,9.198090553283691
+dist_to_lumen,nuclei,7,mean,7.467806816101074
+dist_to_lumen,nuclei,8,mean,7.495289325714111
+dist_to_lumen,nuclei,9,mean,7.984447002410889
+dist_to_lumen,nuclei,10,mean,10.548694610595703
+dist_to_lumen,nuclei,11,mean,7.187387466430664
+dist_to_lumen,nuclei,12,mean,8.405850410461426
+dist_to_lumen,nuclei,13,mean,9.585248947143555
+dist_to_lumen,nuclei,14,mean,8.65551471710205
+dist_to_lumen,nuclei,15,mean,9.393585205078125
+dist_to_lumen,nuclei,16,mean,7.2069621086120605
+dist_to_lumen,nuclei,17,mean,9.467308044433594
+dist_to_lumen,nuclei,18,mean,9.529365539550781
+dist_to_lumen,nuclei,19,mean,7.544955730438232
+dist_to_lumen,nuclei,20,mean,8.24293327331543
+dist_to_basal,nuclei,1,mean,3.480356216430664
+dist_to_basal,nuclei,2,mean,3.0895817279815674
+dist_to_basal,nuclei,3,mean,4.145165920257568
+dist_to_basal,nuclei,4,mean,4.603912830352783
+dist_to_basal,nuclei,5,mean,4.8052263259887695
+dist_to_basal,nuclei,6,mean,4.001973628997803
+dist_to_basal,nuclei,7,mean,3.4609389305114746
+dist_to_basal,nuclei,8,mean,4.6254706382751465
+dist_to_basal,nuclei,9,mean,4.146569728851318
+dist_to_basal,nuclei,10,mean,4.442856788635254
+dist_to_basal,nuclei,11,mean,3.66614031791687
+dist_to_basal,nuclei,12,mean,3.187755823135376
+dist_to_basal,nuclei,13,mean,3.9625508785247803
+dist_to_basal,nuclei,14,mean,5.978910446166992
+dist_to_basal,nuclei,15,mean,3.7076592445373535
+dist_to_basal,nuclei,16,mean,5.013998508453369
+dist_to_basal,nuclei,17,mean,4.201594352722168
+dist_to_basal,nuclei,18,mean,4.226149559020996
+dist_to_basal,nuclei,19,mean,6.444519519805908
+dist_to_basal,nuclei,20,mean,5.720365047454834
+na,nuclei,1,volume,207.26160000000002
+na,nuclei,2,volume,338.67600000000004
+na,nuclei,3,volume,221.99840000000003
+na,nuclei,4,volume,208.07280000000003
+na,nuclei,5,volume,416.41600000000005
+na,nuclei,6,volume,216.72560000000001
+na,nuclei,7,volume,367.06800000000004
+na,nuclei,8,volume,241.8728
+na,nuclei,9,volume,402.22
+na,nuclei,10,volume,330.02320000000003
+na,nuclei,11,volume,180.8976
+na,nuclei,12,volume,192.25440000000003
+na,nuclei,13,volume,229.70480000000003
+na,nuclei,14,volume,441.29280000000006
+na,nuclei,15,volume,369.63680000000005
+na,nuclei,16,volume,404.51840000000004
+na,nuclei,17,volume,348.95120000000003
+na,nuclei,18,volume,406.27600000000007
+na,nuclei,19,volume,577.0336000000001
+na,nuclei,20,volume,426.42080000000004
+na,cell,1,volume,860.4128000000001
+na,cell,2,volume,1081.7352
+na,cell,3,volume,878.3944000000001
+na,cell,4,volume,858.9256000000001
+na,cell,5,volume,1505.8576000000003
+na,cell,6,volume,925.0384000000001
+na,cell,7,volume,1141.0880000000002
+na,cell,8,volume,1065.1056
+na,cell,9,volume,1475.4376000000002
+na,cell,10,volume,1127.9736
+na,cell,11,volume,618.2696000000001
+na,cell,12,volume,665.5896
+na,cell,13,volume,872.4456000000001
+na,cell,15,volume,1238.0264000000002
+na,cell,16,volume,1304.5448000000001
+na,cell,17,volume,1159.8808000000001
+na,cell,18,volume,1528.1656000000003
+na,cell,19,volume,3338.4936000000002
+na,cell,20,volume,1887.9328000000003
+na,epithelium,1,volume,23772.892000000003
+na,lumen,1,volume,725.8888000000001
+na,nuclei,1,mean_radius,1.040822370172954
+na,nuclei,1,max_radius,2.74138651050887
+na,nuclei,2,mean_radius,1.187469782321267
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